{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,5,8]],"date-time":"2026-05-08T19:01:46Z","timestamp":1778266906521,"version":"3.51.4"},"publisher-location":"Cham","reference-count":16,"publisher":"Springer International Publishing","isbn-type":[{"value":"9783319673882","type":"print"},{"value":"9783319673899","type":"electronic"}],"license":[{"start":{"date-parts":[[2017,1,1]],"date-time":"2017-01-01T00:00:00Z","timestamp":1483228800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2017]]},"DOI":"10.1007\/978-3-319-67389-9_42","type":"book-chapter","created":{"date-parts":[[2017,9,6]],"date-time":"2017-09-06T22:18:37Z","timestamp":1504736317000},"page":"362-370","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":172,"title":["Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks"],"prefix":"10.1007","author":[{"given":"Nicha C.","family":"Dvornek","sequence":"first","affiliation":[]},{"given":"Pamela","family":"Ventola","sequence":"additional","affiliation":[]},{"given":"Kevin A.","family":"Pelphrey","sequence":"additional","affiliation":[]},{"given":"James S.","family":"Duncan","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2017,9,7]]},"reference":[{"key":"42_CR1","doi-asserted-by":"publisher","first-page":"736","DOI":"10.1016\/j.neuroimage.2016.10.045","volume":"147","author":"A Abraham","year":"2017","unstructured":"Abraham, A., Milham, M.P., Martino, A.D., Craddock, R.C., Samaras, D., Thirion, B., Varoquaux, G.: Deriving reproducible biomarkers from multi-site resting-state data: an autism-based example. Neuroimage 147, 736\u2013745 (2017)","journal-title":"Neuroimage"},{"key":"42_CR2","doi-asserted-by":"publisher","first-page":"37","DOI":"10.1016\/0010-0277(85)90022-8","volume":"21","author":"S Baron-Cohen","year":"1985","unstructured":"Baron-Cohen, S., Abraham, A., Leslie, M., Frith, U.: Does the autistic child have a \u201ctheory of mind\u201d. Cognition 21, 37\u201346 (1985)","journal-title":"Cognition"},{"key":"42_CR3","doi-asserted-by":"publisher","first-page":"238","DOI":"10.1016\/j.nicl.2015.04.002","volume":"8","author":"CP Chen","year":"2015","unstructured":"Chen, C.P., Keown, C.L., Jahedi, A., Nair, A., Pflieger, M.E., Bailey, B.A., M\u00fcller, R.A.: Diagnostic classification of intrinsic functional connectivity highlights somatosensory, default mode, and visual regions in autism. Neuroimage: Clin. 8, 238\u2013245 (2015)","journal-title":"Neuroimage: Clin."},{"key":"42_CR4","unstructured":"Chollet, F.: Keras (2015). https:\/\/github.com\/fchollet\/keras"},{"key":"42_CR5","unstructured":"Craddock, C., Benhajali, Y., Chu, C., Chouinard, F., Evans, A., Jakab, A., Khundrakpam, B.S., Lewis, J.D., Li, Q., Milham, M., Yan, C., Bellec, P.: The neuro bureau preprocessing initiative: open sharing of preprocessed neuroimaging data and derivatives. In: Neuroinformatics (2013)"},{"key":"42_CR6","doi-asserted-by":"publisher","first-page":"1914","DOI":"10.1002\/hbm.21333","volume":"33","author":"RC Craddock","year":"2012","unstructured":"Craddock, R.C., James, G.A., Holtzheimer, P.E., Hu, X.P., Mayberg, H.S.: A whole brain fMRI atlas generated via spatially constrained spectral clustering, human brain mapping. Hum. Brain Mapp. 33, 1914\u20131928 (2012)","journal-title":"Hum. Brain Mapp."},{"key":"42_CR7","doi-asserted-by":"publisher","first-page":"659","DOI":"10.1038\/mp.2013.78","volume":"19","author":"A Di Martino","year":"2014","unstructured":"Di Martino, A., Yan, C.G., Li, Q., Denio, E., Castellanos, F.X., Alaerts, K., Anderson, J.S., Assaf, M., Bookheimer, S.Y., Dapretto, M., Deen, B., Delmonte, S., Dinstein, I., Ertl-Wagner, B., Fair, D.A., Gallagher, L., Kennedy, D.P., Keown, C.L., Keysers, C., Lainhart, J.E., Lord, C., Luna, B., Menon, V., Minshew, N.J., Monk, C.S., Mueller, S., M\u00fcller, R.A., Nebel, M.B., Nigg, J.T., O\u2019Hearn, K., Pelphrey, K.A., Peltier, S.J., Rudie, J.D., Sunaert, S., Thioux, M., Tyszka, J.M., Uddin, L.Q., Verhoeven, J.S., Wenderoth, N., Wiggins, J.L., Mostofsky, S.H., Milham, M.P.: The autism brain imaging data exchange: towards a large-scale evaluation of the intrinsic brain architecture in autism. Mol. Psychiatry 19, 659\u2013667 (2014)","journal-title":"Mol. Psychiatry"},{"key":"42_CR8","unstructured":"Gal, Y., Ghahramani, Z.: A theoretically grounded application of dropout in recurrent neural networks. In: NIPS (2016)"},{"key":"42_CR9","doi-asserted-by":"crossref","unstructured":"Ghiassian, S., Greiner, R., Jin, P., Brown, M.R.G.: Using functional or structural magnetic resonance images and personal characteristic data to identify adhd and autism. PLOS One 11(12) (2016)","DOI":"10.1371\/journal.pone.0166934"},{"issue":"8","key":"42_CR10","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997)","journal-title":"Neural Comput."},{"key":"42_CR11","doi-asserted-by":"crossref","unstructured":"Lombardo, M.V., Barnes, J.L., Wheelwright, S.J., Baron-Cohen, S.: Self-referential cognition and empathy in autism. PLoS One 2 (2007)","DOI":"10.1371\/journal.pone.0000883"},{"key":"42_CR12","doi-asserted-by":"crossref","unstructured":"Nielsen, J.A., Zielinski, B.A., Fletcher, P.T., Alexander, A.L., Lange, N., Bigler, E.D., Lainhart, J.E., Anderson, J.S.: Multisite functional connectivity MRI classification of autism: abide results. Front. Hum. Neurosci. 7, 599 (2013)","DOI":"10.3389\/fnhum.2013.00599"},{"key":"42_CR13","doi-asserted-by":"publisher","first-page":"359","DOI":"10.1016\/j.nicl.2014.12.013","volume":"7","author":"M Plitt","year":"2015","unstructured":"Plitt, M., Barnes, K.A., Martin, A.: Functional connectivity classification of autism identifies highly predictive brain features but falls short of biomarker standards. Neuroimage: Clin. 7, 359\u2013366 (2015)","journal-title":"Neuroimage: Clin."},{"key":"42_CR14","unstructured":"Preprocessed Connectomes Project: ABIDE Preprocessed. http:\/\/preprocessed-connectomes-project.org\/abide\/"},{"issue":"8","key":"42_CR15","doi-asserted-by":"publisher","first-page":"869","DOI":"10.1001\/jamapsychiatry.2013.104","volume":"70","author":"LQ Uddin","year":"2014","unstructured":"Uddin, L.Q., Supekar, K., Lynch, C.J., Khouzam, A., Phillips, J., Feinstein, C., Menon, V.: Salience network-based classification and prediction of symptom severity in children with autism. JAMA Psychiatry 70(8), 869\u2013879 (2014)","journal-title":"JAMA Psychiatry"},{"key":"42_CR16","doi-asserted-by":"crossref","unstructured":"Yarkoni, T., Poldrack, R.A., Nichols, T.E., Van Essen, D.C., Wager, T.D.: Large-scale automated synthesis of human functional neuroimaging data. Nat. Methods (2011). www.neurosynth.org","DOI":"10.1038\/nmeth.1635"}],"container-title":["Lecture Notes in Computer Science","Machine Learning in Medical Imaging"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-67389-9_42","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2024,3,12]],"date-time":"2024-03-12T18:16:49Z","timestamp":1710267409000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/978-3-319-67389-9_42"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017]]},"ISBN":["9783319673882","9783319673899"],"references-count":16,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-67389-9_42","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"value":"0302-9743","type":"print"},{"value":"1611-3349","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017]]},"assertion":[{"value":"7 September 2017","order":1,"name":"first_online","label":"First Online","group":{"name":"ChapterHistory","label":"Chapter History"}},{"value":"MLMI","order":1,"name":"conference_acronym","label":"Conference Acronym","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"International Workshop on Machine Learning in Medical Imaging","order":2,"name":"conference_name","label":"Conference Name","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Quebec City","order":3,"name":"conference_city","label":"Conference City","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"Canada","order":4,"name":"conference_country","label":"Conference Country","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"2017","order":5,"name":"conference_year","label":"Conference Year","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2017","order":7,"name":"conference_start_date","label":"Conference Start Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"10 September 2017","order":8,"name":"conference_end_date","label":"Conference End Date","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"8","order":9,"name":"conference_number","label":"Conference Number","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"mlmi-med2017","order":10,"name":"conference_id","label":"Conference ID","group":{"name":"ConferenceInfo","label":"Conference Information"}},{"value":"http:\/\/mlmi2017.web.unc.edu\/","order":11,"name":"conference_url","label":"Conference URL","group":{"name":"ConferenceInfo","label":"Conference Information"}}]}}